Everything in Python is an object, and to create new objects, you need the help of object-oriented programming. 

One of the major goals of creating objects is to encapsulate data and the various methods that act on the data into a single thing.

What’s more, creating classes is how to design these objects assign functionality and data to them.

In this article, you’ll discover a simple guide to python object-oriented design with examples and several tips for Python3 object-oriented design and programming.

A simple guide to Python Object with Examples

OOP appeals to users outside the software engineering space and extends to machine learning engineering and data science.

The main concept of OOPs is binding data and functions that work on said data together as one unit. This allows no other part of the code to access the data.

<What Is Object-Oriented Programming in Python3?>

Object-oriented Programming (OOP) in Python are programming models or concepts that use classes and objects in programming. 

Objects in python3 object-oriented programming typically package related behaviors and data into representations of everyday objects. 

In this context, Objects are more like the components of a system, and they contain raw data just like the pre-processed materials at every step of an assembly line. Behavior is the action that each assembly line component performs. 

OOPs typically aim to implement some everyday entities such as encapsulation, inheritance, and even polymorphism in programming.

OOP is based on creating reusable objects that have their behaviors and properties that can be bundled, manipulated, and acted upon as a programming paradigm.

Software engineers, data scientists, and developers worldwide favor python3 object-oriented programming over popular programming languages such as Java, Python, and C++.

Besides making codes logical and reusable, Object-oriented programming makes inheritance simpler to implement while following the DRY principle.

What are the Benefits of OOP?

Object-Oriented programming is quite popular as a coding paradigm, and one of the reasons for its popularity is because it prevents redundancy and ensures code reusability. Below are some benefits of OOP:

• OOP is secure, and it protects vital information through encapsulation.
• It is reusable means you can use OOP objects across programs.
• It is easier to debug OOP, and classes usually contain all the related information.
• It allows for behaviors that are class-specific via polymorphism.
• Object-oriented programming easily models complex things as simple, reproducible structures.
• Troubleshooting is easier with OOP.
• Users can solve problems easier through object-oriented programming because they can break the problem down into easily-solved bit-sized problems.
• Users can upgrade the object-oriented programming system of languages from smaller systems to much larger ones.
• Multiple instances of the same object without interference.

<Instantiate an Object in Python>

Instantiation is one of the many terms you encounter when using Python. What does it mean to instantiate an object? 

For starters, to instantiate means creating an instance by defining a specific variation of an object within a class, giving it a name, and locating it in a physical space/place.

In programming with Python, instantiation creates a real instance of a template or an abstraction like a computer class or objects.

With instantiation, some writers opine that you instantiate a class to create an object or a non-abstract instance of the class.

Meanwhile, the object becomes an executable file that you can run on your computer. Instantiating classes are pretty straightforward in Python.

You only need to call the class like it were a function while passing the arguments that the __init__() method needs. 

Your return value will serve as the newly created object. Here are some steps from IDLE’s interactive window to help you instantiate an object in Python.

• Open the IDLE interactive window and input the following code to create a new Dog class with no methods or attributes. 

>>>

>>> class Dog:

…    pass

• As mentioned, creating a new object from a class is instantiating an object, and you can instantiate a new Dog object by typing the class name. 
• Next, add open and closed parentheses:

>>>

>>> Dog()

<__main__.Dog object at 0x106702d30>

After adding parentheses, you have a new Dog object at 0x106702d30. This unique string of numbers and letters is a memory address.

Memory addresses indicate where you store the Dog object in your computer’s memory. But know that the address you will see on your computer screen will be different. 

• Next, you need to instantiate another Dog object like so:

>>>

>>> Dog()

<__main__.Dog object at 0x0004ccc90>

The location of this new Dog instance is a different memory address, and this is because it is completely a new instance and is entirely unique from the first Dog object we instantiated. You can see this in another way by typing the following:

>>>

>>> a = Dog()

>>> b = Dog()

>>> a == b

False

In this particular code, you create two new Dog objects and assign these objects to variables a and b.

Observe that when comparing a and b with the == operator, your result is False. While a and b are instances of the Dog class, they represent different objects in memory.

<Main Concepts of Object-Oriented Programming>

Beginners prefer Object-oriented languages for some reason. One such reason is that python3 object-oriented programming languages give data the same organization the human brain gives to information.

Of course, OOP doesn’t act in isolation, and it relies on several concepts to remain as efficient and effective as possible. Below, we explain some main concepts of python object-oriented design.

#1. Class

Classes are abstract blueprints you can use to create more concrete and specific objects. Often, classes represent broad categories that share attributes, such as Dog, Cat, or Car.

One noteworthy thing about classes is that they define what attributes an instance will have, such as color, but they don’t define the value of those attributes for a specific object.

Also, classes can contain functions, and these functions known as methods are available only to objects of that type in python object oriented designs.

Functions are well defined within the class, and they carry out some actions that help that particular type of object. 

#2. Objects

An object is an entity with behavior and a state associated with it. An object may be a real-world object such as a keyboard, pen, table, chair, etc.

Strings, floating-point numbers, integers, dictionaries, and arrays are all examples of objects. In other words, any single string or single integer is an object.

We’ve all been using objects without even knowing. The number 13 is an object, and a list is also an object that carries other objects. Below are what an object consists of:

• Behavior: The methods of an object describes its behavior. What’s more, behavior also mirrors the response of an object to other objects.
• State: The attributes of an object are what represent and describe its state, and it is what reflects the properties of said object.
• Identity: An identity provides a unique name to an object, allowing one object to interact with others.

These concepts can be confusing for beginners, so here is a quick example to demonstrate what we mean.

• The name of a cat can be considered its Identity.
• The behavior describes actions like feeding, sleeping, meowing.
• Attributes or states can be considered as the age, breed, or color of the dog.

#3. Polymorphism

The term polymorphism in python3 object oriented programming simply refers to having several forms, and as a concept, it permits the uniform treatment of classes within a hierarchy.

It simply means that many several methods can do the same tasks, so users need to write calling codes to handle objects from the root of the hierarchy.

Any object that any child class instantiates in the hierarchy will be handled the same way in the python object oriented design.

Derived objects share similar interfaces as their parents; calling codes can call functions in the interface of that class.

However, at run-time, the suitable function will be called, and this all depends on the type of object passed, leading to different behaviors.

Here is an example of Polymorphism in Python:

class Bird:

def intro(self):

print(“There are many types of birds.”)

def flight(self):

print(“Most of the birds can fly but some cannot.”)

class sparrow(Bird):

def flight(self):

print(“Sparrows can fly.”)

class ostrich(Bird):

def flight(self):

print(“Ostriches cannot fly.”)

obj_bird = Bird()

obj_spr = sparrow()

obj_ost = ostrich()

obj_bird.intro()

obj_bird.flight()

obj_spr.intro()

obj_spr.flight()

obj_ost.intro()

obj_ost.flight()

Output

There are many types of birds.

Most of the birds can fly but some cannot.

There are many types of birds.

Sparrows can fly.

There are many types of birds.

Ostriches cannot fly.

#4. Encapsulation

In python3 object oriented programming, encapsulation is arguably one of the fundamental concepts.

It represents the idea of wrapping data and the several methods that work on the data within a single unit.

This alone restricts accessing methods and variables directly and can stop the spontaneous modification of data.

To prevent such accidental change, only an object’s method can change the variable of said object.

These variables are called private variables. One good example of encapsulation is a class because it encapsulates every data, variable, member function, and more.

Here is OOP examples Python Encapsulation:

# Python program to

# demonstrate private members

# Creating a Base class

class Base:

def __init__(self):

self.a = “GeeksforGeeks”

self.__c = “GeeksforGeeks”

# Creating a derived class

class Derived(Base):

def __init__(self):

# Calling constructor of

# Base class

Base.__init__(self)

print(“Calling private member of base class: “)

print(self.__c)

# Driver code

obj1 = Base()

print(obj1.a)

# Uncommenting print(obj1.c) will

# raise an AttributeError

# Uncommenting obj2 = Derived() will

# also raise an AtrributeError as

# private member of base class

# is called inside derived class

Output

GeeksforGeeks

#5. Inheritance

Another important concept in python3 object oriented programming is Inheritance which is the capacity of a class to derive or even inherit the properties from another class.

It is simply the parent/child relationship between classes as child classes can inherit the data or behaviors from a parent class.

We call the class that does the inheriting or deriving the child class or derived class, while the class from which properties are being derived is the parent class or base class. Inheritance  has several benefits, and these are some of them:

• Inheritance is transitive, meaning that if class B inherits from another class, A, then all subclasses of class B will automatically inherit from class A
• Inheritance represents real-world relationships, and it does it well.
• It also provides the reusability of a code. This means that we do not need to write the same code repeatedly 
• Inheritance permits users to add more features to a class without changing it.

Here is OOP Examples Python Inheritance:

# Python code to demonstrate how parent constructors

# are called.

# parent class

class Person(object):

# __init__ is known as the constructor

def __init__(self, name, idnumber):

self.name = name

self.idnumber = idnumber

def display(self):

print(self.name)

print(self.idnumber)

def details(self):

print(“My name is {}”.format(self.name))

print(“IdNumber: {}”.format(self.idnumber))

# child class

class Employee(Person):

def __init__(self, name, idnumber, salary, post):

self.salary = salary

self.post = post

# invoking the __init__ of the parent class

Person.__init__(self, name, idnumber)

def details(self):

print(“My name is {}”.format(self.name))

print(“IdNumber: {}”.format(self.idnumber))

print(“Post: {}”.format(self.post))

# creation of an object variable or an instance

a = Employee(‘Rahul’, 886012, 200000, “Intern”)

# calling a function of the class Person using

# its instance

a.display()

a.details(

Output

Rahul

886012

My name is Rahul

IdNumber: 886012

Post: Intern

Here, we have created two classes, a parent class called Person and a child class called Employee in our OOP examples python above. 

The Employee class inherits from our Person class, and we can use the methods of our Person class via Employee class.

What’s more, a child class can modify the behavior of the parent class, as we can see from the details() method.

Other Concepts and Terms Used in Python Object Oriented Design

#1. Composition

Composition is another term used in python object oriented design and it describes the relationship where an object contains other objects as part of its state and is a way to achieve association.

We can use composition in place of inheritance to give behavior and attributes to a class instead of forcing inheritance to provide the desired behavior.

We’ve already used the composition concept when we give class attributes: strings and integers. However, we can go a step further by creating custom classes we can use as attributes while composing behavior into classes.

When we use composition, we get a means to add behavior and attributes to a class without having having to make contrived hierarchies of inheritance.

There is a solid relationship between the dependent object and the containing object with composition. 

In other words, it is the state where the containing objects don’t have an independent existence. So if you delete a parent object, all the child objects get deleted automatically.

#2. Aggregation

Aggregation represents the unique relationship where one object contains other objects as a part of its state.

It is referred to the weak relationship that exists between objects. In Java, it is termed a has-a relationship and is another way to reuse objects.

#3. Coupling

Coupling also an important term for python object oriented design and it is the information, knowledge, or dependency of another class. It exists because classes are aware of each other. If a class has the details of another class, there is a substantial coupling. 

#4. Association

Association describes the relationship existing between objects. For instance, one object can be associated with another or many objects. 

Four types of association exist between objects: One to One, One to Many, Many to One, and Many to Many. Association can be unidirectional or bidirectional.

#5. Cohesion

Cohesion describes the level of a component that performs one well-defined task. We can do this well-defined task by a highly cohesive method too. So the weakly cohesive method gets to split the task into different parts in python object oriented designing.

<Class Definition>

To create a class in Python, users can use the class keyword. What’s more, we also use a property given below:

class MyClass:

  x = 4

To create an object like the one below, we use MyClass

p1 = MyClass()

print(p1.x)

For instance, suppose a businessman contract you to make an online store for a sneakers store.

Python can help us define a Sneaker class and the properties that every sneaker must have listed on the online store site. What do we do?

• We use the class keyword to start our class and then set the name to Sneaker. Know that every instance of Sneaker will represent a different pair of sneakers.
• Next, we list the properties we want each sneaker to have, including material, size, price, and isOnSale.
• Then we set each property to the value None, and we will set each of the property values when we initialize a Sneaker object.

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class Sneaker:

    # define the properties and assign none value

    size = None

    isOnSale= None

    material = None

    price = None

Remember that you need to include four spaces before every method or property within a class. We do this so that Python can recognize they are all within the defined class.

Tips for Python3 Object-Oriented Design and Programming

#1. Set Attributes in the Constructor

Setting attributes in the constructor ensures they will always exist and be defined in a single place. Python gives a convenient way to do this using the _init_() Python object constructor.

Adding this method to the class will execute automatically as soon as an instance of the object is created. The Python object constructor is great for imposing different checks on attribute values.

#2. Distinguish Class-level and Instance-level Data and Methods

Instant-level data shouldn’t interfere with how a class works in general. It should be kept separate from the class-level data. We can use class-level methods to create a class instance from external sources such as CSV files.

#3. Make Sure to Determine What is Equal

When you compare two instances of a particular object, Python observes the memory chunks that they occupy. So to get meaningful comparisons, you need to define what is meant by equality explicitly.

#4. Offer String Representations

When you define the reproducible representations and string for the object, you make it human-readable when printed and easy to regurgitate.

#5. Figure out What Static is

Marking functions as static explicitly goes a long way in saving memory and improving the code readability.

#6. Decide what is Private and Internal

Python uses a leading underscore for naming internal methods and attributes, and a double leading underscore marks private ones. Deciding this will let your code users know which part of the code is not part of the public API and shouldn’t be relied on.

#7. Set Access to Attributes

The next tip we could use is to set access to attributes. Make use of setters and properties to make attributes read-only while validating their updates.

#8. Make Use of Docstrings

Another tip for Python3 Object-oriented design and programming is the use of docstrings. It helps to understand the code when working with it for the first time.

Docstrings tend not to be outdated quickly compared to external documentation in the form of “readme.”

Write docstrings for every public module, class, method, and function. Docstrings aren’t needed for non-public methods.

However, you should use a comment that describes what the method does, and it should appear after the “def” line.

Conclusion

Object-oriented programming needs critically thinking about the program’s structure and planning at the start of coding.

OOP focuses on breaking up the requirements into easy and reusable classes that users can use to blueprint instances of objects.

Implementing OOP permits better data structures that help you save time in the long run but understanding the different OOPS is essential in thriving at software development.